Optical Character Recognition (OCR) offers excellent productivity gains over manual data entry. No OCR algorithm can identify 100% of all characters ever presented. There will always be those characters deemed "unrecognizable" or "uncertain". How we deal with these recognition uncertainties which are referred to as reject/reentry depends on the particular application. In general, one of two approaches is used: (1) the OCR algorithm makes its best guess on all characters and any corrections or edits are made by proofreading or using electronic spell-checking, or (2) the OCR algorithm flags those characters deemed uncertain and a human operator corrects those errors based on the original document or an image of that document.
The first approach works quite well for letters, memos, or other documents with contextual information (i.e. words with known spelling). However, most documents encountered in the business world are forms. These can be claims forms, remittance documents, bills, order forms, checks, etc. Unfortunately, these documents offer very little contextual information, since the pertinent information consists of proper names, addresses, dollar amounts, insurance numbers, or account numbers. Therefore, the second approach of reject/reentry is more appropriate for these applications.
Once the OCR algorithm is instructed to flag all uncertain characters, a reject/reentry system is required, where an operator can correct and/or confirm the uncertain characters. Currently, there are three ways of accomplishing this: (1) Go back to the original paper document, (2) use a microfilm image of the document as a reference, or (3) use an electronic image as a reference. Of these choices, (1) is the easiest to implement (but also the most labor intensive), (3) is the most difficult to implement (but requires the least amount of labor) and (2) is somewhere in between. Most of today's state-of-the-art OCR systems use electronic imaging for reject/reentry.
Although electronic imaging offers the highest productivity for reject/reentry, how the system is implemented plays a major role in operator efficiency, data integrity, and the resulting productivity gain. The most popular method of displaying the reject/reentry information on a computer screen consists of a video window 10 to display the image of the uncertain character(s) and a line of ASCII data 12 to display the OCR results as shown in FIG. 1. The operator looks at the ASCII data and finds the uncertain character usually highlighted or replaced by a "?" 14, and then looks up at the video window 10 for that field, and finds the corresponding character. The operator then types the correct character using the keyboard. Usually the entire field (such as the name field) is displayed in the video field in order to give the operator some context (for example, deciding between a "0" or an "o" may depend on whether that character's neighbors were letters or numbers). However, looking back and forth between the video window 10 and the ASCII data 12 (FIG. 1) is time consuming and can cause operator fatigue. Also, displaying an entire field of video for each uncertain character slows down screen updates because of the additional information that must be written on the screen. This also means increased data, requiring increased disk storage, as well as longer data transmission times, thereby adding further inefficiencies. One way to minimize operator fatigue is to speed up the correction process so as to reduce the amount of data required for the Video Display Window. This may be accomplished by using an "Embedded Video Window", that carries a bit map image of the unrecognizable character.